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The prediction results from a call to DetectAnomalies. DetectAnomalyResult includes classification information for the prediction (IsAnomalous and Confidence). If the model you use is an image segementation model, DetectAnomalyResult also includes segmentation information (Anomalies and AnomalyMask). Classification information is calculated separately from segmentation information and you shouldn't assume a relationship between them.

See: newDetectAnomalyResult smart constructor.

Create a value of DetectAnomalyResult with all optional fields omitted.

Use generic-lens or optics to modify other optional fields.

The following record fields are available, with the corresponding lenses provided for backwards compatibility:

$sel:anomalies:DetectAnomalyResult', detectAnomalyResult_anomalies - If the model is an image segmentation model, Anomalies contains a list of anomaly types found in the image. There is one entry for each type of anomaly found (even if multiple instances of an anomaly type exist on the image). The first element in the list is always an anomaly type representing the image background ('background') and shouldn't be considered an anomaly. Amazon Lookout for Vision automatically add the background anomaly type to the response, and you don't need to declare a background anomaly type in your dataset.

If the list has one entry ('background'), no anomalies were found on the image.

An image classification model doesn't return an Anomalies list.

$sel:anomalyMask:DetectAnomalyResult', detectAnomalyResult_anomalyMask - If the model is an image segmentation model, AnomalyMask contains pixel masks that covers all anomaly types found on the image. Each anomaly type has a different mask color. To map a color to an anomaly type, see the color field of the PixelAnomaly object.

An image classification model doesn't return an Anomalies list.-- -- Note: This Lens automatically encodes and decodes Base64 data. -- The underlying isomorphism will encode to Base64 representation during -- serialisation, and decode from Base64 representation during deserialisation. -- This Lens accepts and returns only raw unencoded data.

$sel:confidence:DetectAnomalyResult', detectAnomalyResult_confidence - The confidence that Lookout for Vision has in the accuracy of the classification in IsAnomalous.

$sel:isAnomalous:DetectAnomalyResult', detectAnomalyResult_isAnomalous - True if Amazon Lookout for Vision classifies the image as containing an anomaly, otherwise false.

$sel:source:DetectAnomalyResult', detectAnomalyResult_source - The source of the image that was analyzed. direct means that the images was supplied from the local computer. No other values are supported.

If the model is an image segmentation model, Anomalies contains a list of anomaly types found in the image. There is one entry for each type of anomaly found (even if multiple instances of an anomaly type exist on the image). The first element in the list is always an anomaly type representing the image background ('background') and shouldn't be considered an anomaly. Amazon Lookout for Vision automatically add the background anomaly type to the response, and you don't need to declare a background anomaly type in your dataset.

If the list has one entry ('background'), no anomalies were found on the image.

An image classification model doesn't return an Anomalies list.

If the model is an image segmentation model, AnomalyMask contains pixel masks that covers all anomaly types found on the image. Each anomaly type has a different mask color. To map a color to an anomaly type, see the color field of the PixelAnomaly object.

An image classification model doesn't return an Anomalies list.-- -- Note: This Lens automatically encodes and decodes Base64 data. -- The underlying isomorphism will encode to Base64 representation during -- serialisation, and decode from Base64 representation during deserialisation. -- This Lens accepts and returns only raw unencoded data.

The confidence that Lookout for Vision has in the accuracy of the classification in IsAnomalous.

True if Amazon Lookout for Vision classifies the image as containing an anomaly, otherwise false.

The source of the image that was analyzed. direct means that the images was supplied from the local computer. No other values are supported.